t = Time(now)
filenames = []
for i in range(100):
SN = 2. # + i
weights = list(np.linspace(0.00001, 1, len(xy)))
m = simtools.delta_point(N, center=False, xy=xy, weights=weights)
im = simtools.image(m, N, t_exp=1, X_FWHM=FWHM, SN=SN, bkg_pdf='gaussian')
filenames.append(
simtools.capsule_corp(im, t, t_exp=1, i=i, zero=3.1415, path=test_dir))
S = np.zeros(shape=(N,N))
psf = simtools.Psf(N, FWHM)
for afile in filenames:
px = pc.SingleImage(afile)
# Now I must combine this images, normalizing by the var(noise)
var = px.meta['std']
conv = convolve_fft(px.imagedata, psf)
S = S + conv/var**2.
fits.writeto(data=S, filename='./test_images/S.fits', overwrite=True)
swarp = shlex.split('swarp @test_images/one_star/imagelist.txt -c default.swarp')
subprocess.call(swarp)
plt.figure()
plt.subplot(121)
plt.imshow(S, interpolation='none')
plt.title('Ofek')
plt.subplot(122)
y = np.linspace(6 * max_fw, N - 6 * max_fw, 7)
xy = simtools.cartesian_product([x, y])
SN = 1000. # SN para poder medir psf
weights = list(np.linspace(10, 100, len(xy)))
m = simtools.delta_point(N, center=False, xy=xy, weights=weights)
im = simtools.image(m,
N,
t_exp,
X_FWHM,
SN,
Y_FWHM=Y_FWHM,
theta=theta,
bkg_pdf='poisson')
sim = pc.SingleImage(im, imagefile=False, sim=True)
fitted_models = sim.fit_psf_sep()
x_sds = [g.x_stddev for g in fitted_models]
y_sds = [g.y_stddev for g in fitted_models]
th = [g.theta * 180 / np.pi for g in fitted_models]
amplitudes = [g.amplitude for g in fitted_models]
fwhm_x = 2.335 * np.mean(x_sds)
fwhm_y = 2.335 * np.mean(y_sds)
mean_th = round(np.mean(th))
fwhm = max(fwhm_x, fwhm_y)
print('X Fwhm = {}, Y Fwhm = {}, Mean Theta = {}'.format(
fwhm_x, fwhm_y, mean_th))
SN = 5. # SN para poder medir psf
weights = list(np.linspace(10, 1000., len(xy)))
m = simtools.delta_point(N, center=False, xy=xy, weights=weights)
im = simtools.image(m,
N,
t_exp,
X_FWHM,
Y_FWHM=Y_FWHM,
theta=theta,
SN=SN,
bkg_pdf='poisson')
frames.append(im + 100.)
frame = np.zeros((1024, 1024))
for j in range(2):
for i in range(2):
frame[i * 512:(i + 1) * 512, j * 512:(j + 1) * 512] = frames[i + 2 * j]
with pc.SingleImage(frame, sim=True, imagefile=False) as sim:
a_fields, psf_basis = sim.get_variable_psf(pow_th=0.01)
plt.imshow(np.log(frame), interpolation='none')
plt.colorbar()
plt.savefig(os.path.join(test_dir, 'test_frame.png'))
plt.close()
utils.plot_psfbasis(psf_basis, path=os.path.join(test_dir, 'psf_basis.png'))
utils.plot_afields(a_fields,
shape=(1024, 1024),
path=os.path.join(test_dir, 'a_fields.png'))
import sep
from astropy.io import fits
from properimage.tests import simtools
from properimage import propercoadd as pc
from properimage import utils
# =============================================================================
# PSF measure test by propercoadd
# =============================================================================
N = 512
test_dir = os.path.abspath('./test/test_images/rebuild_psf2')
frame = utils.sim_varpsf(400, test_dir, SN=5.)
with pc.SingleImage(frame) as sim:
a_fields, psf_basis = sim.get_variable_psf()
utils.plot_afields(a_fields, frame.shape, os.path.join(test_dir, 'a_fields.png'))
utils.plot_psfbasis(psf_basis, os.path.join(test_dir, 'psf_basis.png'), nbook=False)
plt.imshow(np.log10(frame), interpolation='none')
#plt.plot(cat['sources']['x'], cat['sources']['y'], '.k')
plt.colorbar()
plt.tight_layout()
plt.savefig(os.path.join(test_dir, 'test_frame.png'))
plt.close()
cat = sep.extract(frame - sep.Background(frame),
thresh=4.5*sep.Background(frame).globalrms)
xy = [(int(row['y']), int(row['x'])) for row in cat]
reload(pc)
# =============================================================================
# PSF measure test by propercoadd
# =============================================================================
datapath = os.path.abspath('/home/bruno/Documentos/Data/ESO085-030')
frame = os.path.join(datapath, 'eso085-030-030.fit')
d = fits.getdata(frame)
utils.plot_S(d, path='./test/test_images/real_image_test/frame.png')
#fitted_models = sim.fit_psf_sep()
# =============================================================================
# PSF spatially variant
# =============================================================================
with pc.SingleImage(frame, imagefile=True) as sim:
a_f, psf_b = sim.get_variable_psf(pow_th=0.01)
S = sim.s_component
utils.plot_psfbasis(psf_b,
path='./test/test_images/real_image_test/psf_basis.png')
utils.plot_afields(a_f,
S.shape,
path='./test/test_images/real_image_test/a_fields.png')
utils.plot_S(S, path='./test/test_images/real_image_test/S.png')